An In Silico Vaccine Discovery Pipeline for Eukaryotic Pathogens Based on Reverse Vaccinology - Stephen Goodswen
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An In Silico Vaccine Discovery Pipeline for Eukaryotic Pathogens Based on Reverse Vaccinology - Stephen Goodswen

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Reverse vaccinology starts with the genome of the pathogen rather than the pathogen itself. Effectively the wet laboratory in the traditional culture-based approach to cultivate, dissect, and......

Reverse vaccinology starts with the genome of the pathogen rather than the pathogen itself. Effectively the wet laboratory in the traditional culture-based approach to cultivate, dissect, and identify antigens is replaced by bioinformatics. The laboratory validation commences with an unbiased list of all potential antigens that can be expressed by the pathogen, irrespective of life cycle stages and environmental stimuli. There are essentially four steps to reverse vaccinology: 1) predict genes within the genome of the pathogen, 2) convert gene predictions to protein sequences, 3) predict protein characteristics (i.e. potential evidence such as subcellular location, presence of secretory signal peptides and transmembrane helices) given protein sequences, and 4) collect evidence and make an informed decision as to a protein’s suitability as a vaccine candidate.

Authors: Reverse vaccinology starts with the genome of the pathogen rather than the pathogen itself. Effectively the wet laboratory in the traditional culture-based approach to cultivate, dissect, and identify antigens is replaced by bioinformatics. The laboratory validation commences with an unbiased list of all potential antigens that can be expressed by the pathogen, irrespective of life cycle stages and environmental stimuli. There are essentially four steps to reverse vaccinology: 1) predict genes within the genome of the pathogen, 2) convert gene predictions to protein sequences, 3) predict protein characteristics (i.e. potential evidence such as subcellular location, presence of secretory signal peptides and transmembrane helices) given protein sequences, and 4) collect evidence and make an informed decision as to a protein’s suitability as a vaccine candidate.

Authors: Stephen Goodswen, Paul Kennedy, John Ellis

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  • 1. Stephen Goodswen, Paul Kennedy and John Ellis First step in an in silico vaccine discovery pipeline for eukaryotic pathogens Genome Bioinformatics Identify components ? ? ? ? ? ? ? Potential antigens Vaccine development Animal testing Laboratory validation Vaccine candidates 1